| dc.description.abstract | Complexity plays an important role in understanding and working with a
program, and has been measured in many different ways for software applications. The
use of statistical analysis is one of the ways to predict the pattern of complexity among
the modules present in a software application. A random sample of twelve software
applications was selected for this study to examine complexity. A single pair of
complexity measures was evaluated. This pair of complexity measures was the indegrees and out-degrees for each module of an application. The next step was to try to
fit suitable statistical distributions to the in-degrees and to the out-degrees. By using
various statistical distributions such as the normal, log-normal, exponential, geometric,
uniform, poisson and the chi-square, we try to determine the type of distribution for the
in-degrees and the type of distribution for out-degrees of the modules present in the
software applications so that the pattern of complexity can be derived. The chi-square
goodness of fit test was used to test various null hypotheses about the distributions for
the in-degrees and for the out-degrees. Results showed that the pattern of in-degrees and
the pattern of out-degrees both followed chi-square distributions. | en_US |
